PROJECT SUMMARY Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with life-long deficits in communication and social engagement. Among these deficits is impaired pragmatic expression, or the inappropriate use of language in a given context. Because of the pragmatic difficulties they experience, individuals with ASD face challenges in establishing interpersonal relationships, maintaining satisfactory employment, and achieving independence. Despite the impact that deficits in pragmatic expression have on the outcomes of individuals with ASD, researchers do not agree on precisely what functions are impaired, particularly in high-functioning adults. Analyzing spontaneous spoken language is the most effective way to reveal these impairments, but the resources and expertise required for such analysis have thus far made this approach impractical. In this project, we propose using computational language analysis methods to convert speech into text transcripts and to automatically identify specific areas of pragmatic deficit in those transcripts. We explore these methods using spoken language data we will collect from high-functioning verbal adults with ASD and with typical development. In the course of this project, we will investigate: (1) the precise pragmatic functions that are affected in high- functioning adults with ASD; (2) the extent to which these and other reported pragmatic deficits are observed in individuals with ASD regardless of age; and (3) the accuracy of our novel computational methods for extracting these metrics from spontaneous spoken language samples. While achieving these aims, we will explore the utility of automated analysis of spoken language, setting the stage for a future proposal to develop an automated software tool for analyzing spoken language to identify specific areas of deficit in pragmatic expression. A tool for automatically identifying strengths and weaknesses in pragmatic expression could offer utility not only to researchers investigating language functioning in ASD but also to clinicians tasked with diagnosis and health professionals working to develop targeted therapies and interventions. Such interventions could lead to more favorable social outcomes for individuals of all ages with ASD and higher rates of employment among adults with ASD, potentially yielding reductions in costs associated with and resources allocated for serving the needs of this special population.